Overview

Brought to you by YData

Dataset statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Number of variables1414
Number of observations418907391
Missing cells00
Missing cells (%)0.0%0.0%
Duplicate rows00
Duplicate rows (%)0.0%0.0%
Total size in memory4.8 MiB866.1 KiB
Average record size in memory120.0 B120.0 B

Variable types

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Numeric55
Categorical77
Text22

Alerts

Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
booking_complete has constant value "0" booking_complete has constant value "1" Constant
trip_type is highly imbalanced (93.8%) trip_type is highly imbalanced (97.8%) Imbalance
flight_hour has 1321 (3.2%) zeros flight_hour has 180 (2.4%) zeros Zeros
Alert not present in this datasetsales_channel is highly imbalanced (59.9%) Imbalance

Reproduction

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Analysis started2024-12-24 09:11:23.0247462024-12-24 09:11:28.147888
Analysis finished2024-12-24 09:11:28.1349402024-12-24 09:11:31.892330
Duration5.11 seconds3.74 seconds
Software versionydata-profiling vv4.12.1ydata-profiling vv4.12.1
Download configurationconfig.jsonconfig.json

Variables

num_passengers
Real number (ℝ)

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct99
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean1.57989971.6484914
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum11
Maximum99
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
2024-12-24T10:11:32.904195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum11
5-th percentile11
Q111
median11
Q322
95-th percentile44
Maximum99
Range88
Interquartile range (IQR)11

Descriptive statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Standard deviation1.00791911.0622557
Coefficient of variation (CV)0.637963980.64438047
Kurtosis10.2680549.1007124
Mean1.57989971.6484914
Median Absolute Deviation (MAD)00
Skewness2.71186512.5618443
Sum6618212184
Variance1.0159011.1283871
MonotonicityNot monotonicNot monotonic
2024-12-24T10:11:33.004870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 26476
63.2%
2 10640
25.4%
3 2396
 
5.7%
4 1494
 
3.6%
5 438
 
1.0%
6 228
 
0.5%
7 91
 
0.2%
8 76
 
0.2%
9 51
 
0.1%
ValueCountFrequency (%)
1 4403
59.6%
2 2029
27.5%
3 486
 
6.6%
4 273
 
3.7%
5 106
 
1.4%
6 53
 
0.7%
7 16
 
0.2%
9 13
 
0.2%
8 12
 
0.2%
ValueCountFrequency (%)
1 26476
63.2%
2 10640
25.4%
3 2396
 
5.7%
4 1494
 
3.6%
5 438
 
1.0%
6 228
 
0.5%
7 91
 
0.2%
8 76
 
0.2%
9 51
 
0.1%
ValueCountFrequency (%)
1 4403
59.6%
2 2029
27.5%
3 486
 
6.6%
4 273
 
3.7%
5 106
 
1.4%
6 53
 
0.7%
7 16
 
0.2%
8 12
 
0.2%
9 13
 
0.2%
ValueCountFrequency (%)
1 4403
10.5%
2 2029
4.8%
3 486
 
1.2%
4 273
 
0.7%
5 106
 
0.3%
6 53
 
0.1%
7 16
 
< 0.1%
8 12
 
< 0.1%
9 13
 
< 0.1%
ValueCountFrequency (%)
1 26476
358.2%
2 10640
144.0%
3 2396
 
32.4%
4 1494
 
20.2%
5 438
 
5.9%
6 228
 
3.1%
7 91
 
1.2%
8 76
 
1.0%
9 51
 
0.7%

sales_channel
Categorical

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
Internet
37115 
Mobile
4775 
Internet
6802 
Mobile
 
589

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length88
Median length88
Mean length7.7720227.840617
Min length66

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters32557057950
Distinct characters1010
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st rowInternetInternet
2nd rowInternetInternet
3rd rowInternetInternet
4th rowInternetMobile
5th rowInternetInternet

Common Values

ValueCountFrequency (%)
Internet 37115
88.6%
Mobile 4775
 
11.4%
ValueCountFrequency (%)
Internet 6802
92.0%
Mobile 589
 
8.0%

Length

2024-12-24T10:11:33.135756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report: Incomplete Bookings

2024-12-24T10:11:33.257265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:33.302733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
internet 37115
88.6%
mobile 4775
 
11.4%
ValueCountFrequency (%)
internet 6802
92.0%
mobile 589
 
8.0%

Most occurring characters

ValueCountFrequency (%)
e 79005
24.3%
n 74230
22.8%
t 74230
22.8%
I 37115
11.4%
r 37115
11.4%
M 4775
 
1.5%
o 4775
 
1.5%
b 4775
 
1.5%
i 4775
 
1.5%
l 4775
 
1.5%
ValueCountFrequency (%)
e 14193
24.5%
n 13604
23.5%
t 13604
23.5%
I 6802
11.7%
r 6802
11.7%
M 589
 
1.0%
o 589
 
1.0%
b 589
 
1.0%
i 589
 
1.0%
l 589
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 325570
100.0%
ValueCountFrequency (%)
(unknown) 57950
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 79005
24.3%
n 74230
22.8%
t 74230
22.8%
I 37115
11.4%
r 37115
11.4%
M 4775
 
1.5%
o 4775
 
1.5%
b 4775
 
1.5%
i 4775
 
1.5%
l 4775
 
1.5%
ValueCountFrequency (%)
e 14193
24.5%
n 13604
23.5%
t 13604
23.5%
I 6802
11.7%
r 6802
11.7%
M 589
 
1.0%
o 589
 
1.0%
b 589
 
1.0%
i 589
 
1.0%
l 589
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 325570
100.0%
ValueCountFrequency (%)
(unknown) 57950
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 79005
24.3%
n 74230
22.8%
t 74230
22.8%
I 37115
11.4%
r 37115
11.4%
M 4775
 
1.5%
o 4775
 
1.5%
b 4775
 
1.5%
i 4775
 
1.5%
l 4775
 
1.5%
ValueCountFrequency (%)
e 14193
24.5%
n 13604
23.5%
t 13604
23.5%
I 6802
11.7%
r 6802
11.7%
M 589
 
1.0%
o 589
 
1.0%
b 589
 
1.0%
i 589
 
1.0%
l 589
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 325570
100.0%
ValueCountFrequency (%)
(unknown) 57950
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 79005
24.3%
n 74230
22.8%
t 74230
22.8%
I 37115
11.4%
r 37115
11.4%
M 4775
 
1.5%
o 4775
 
1.5%
b 4775
 
1.5%
i 4775
 
1.5%
l 4775
 
1.5%
ValueCountFrequency (%)
e 14193
24.5%
n 13604
23.5%
t 13604
23.5%
I 6802
11.7%
r 6802
11.7%
M 589
 
1.0%
o 589
 
1.0%
b 589
 
1.0%
i 589
 
1.0%
l 589
 
1.0%

trip_type
Categorical

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct33
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
RoundTrip
41413 
OneWay
 
366
CircleTrip
 
111
RoundTrip
7366 
OneWay
 
20
CircleTrip
 
5

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length1010
Median length99
Mean length8.97643838.9925585
Min length66

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters37602366464
Distinct characters1717
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st rowRoundTripRoundTrip
2nd rowRoundTripRoundTrip
3rd rowRoundTripRoundTrip
4th rowRoundTripRoundTrip
5th rowRoundTripRoundTrip

Common Values

ValueCountFrequency (%)
RoundTrip 41413
98.9%
OneWay 366
 
0.9%
CircleTrip 111
 
0.3%
ValueCountFrequency (%)
RoundTrip 7366
99.7%
OneWay 20
 
0.3%
CircleTrip 5
 
0.1%

Length

2024-12-24T10:11:33.400004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report: Incomplete Bookings

2024-12-24T10:11:33.468627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:33.523283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
roundtrip 41413
98.9%
oneway 366
 
0.9%
circletrip 111
 
0.3%
ValueCountFrequency (%)
roundtrip 7366
99.7%
oneway 20
 
0.3%
circletrip 5
 
0.1%

Most occurring characters

ValueCountFrequency (%)
n 41779
11.1%
r 41635
11.1%
i 41635
11.1%
p 41524
11.0%
T 41524
11.0%
o 41413
11.0%
R 41413
11.0%
d 41413
11.0%
u 41413
11.0%
e 477
 
0.1%
Other values (7) 1797
 
0.5%
ValueCountFrequency (%)
n 7386
11.1%
r 7376
11.1%
i 7376
11.1%
p 7371
11.1%
T 7371
11.1%
o 7366
11.1%
R 7366
11.1%
d 7366
11.1%
u 7366
11.1%
e 25
 
< 0.1%
Other values (7) 95
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 376023
100.0%
ValueCountFrequency (%)
(unknown) 66464
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 41779
11.1%
r 41635
11.1%
i 41635
11.1%
p 41524
11.0%
T 41524
11.0%
o 41413
11.0%
R 41413
11.0%
d 41413
11.0%
u 41413
11.0%
e 477
 
0.1%
Other values (7) 1797
 
0.5%
ValueCountFrequency (%)
n 7386
11.1%
r 7376
11.1%
i 7376
11.1%
p 7371
11.1%
T 7371
11.1%
o 7366
11.1%
R 7366
11.1%
d 7366
11.1%
u 7366
11.1%
e 25
 
< 0.1%
Other values (7) 95
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 376023
100.0%
ValueCountFrequency (%)
(unknown) 66464
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 41779
11.1%
r 41635
11.1%
i 41635
11.1%
p 41524
11.0%
T 41524
11.0%
o 41413
11.0%
R 41413
11.0%
d 41413
11.0%
u 41413
11.0%
e 477
 
0.1%
Other values (7) 1797
 
0.5%
ValueCountFrequency (%)
n 7386
11.1%
r 7376
11.1%
i 7376
11.1%
p 7371
11.1%
T 7371
11.1%
o 7366
11.1%
R 7366
11.1%
d 7366
11.1%
u 7366
11.1%
e 25
 
< 0.1%
Other values (7) 95
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 376023
100.0%
ValueCountFrequency (%)
(unknown) 66464
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 41779
11.1%
r 41635
11.1%
i 41635
11.1%
p 41524
11.0%
T 41524
11.0%
o 41413
11.0%
R 41413
11.0%
d 41413
11.0%
u 41413
11.0%
e 477
 
0.1%
Other values (7) 1797
 
0.5%
ValueCountFrequency (%)
n 7386
11.1%
r 7376
11.1%
i 7376
11.1%
p 7371
11.1%
T 7371
11.1%
o 7366
11.1%
R 7366
11.1%
d 7366
11.1%
u 7366
11.1%
e 25
 
< 0.1%
Other values (7) 95
 
0.1%

purchase_lead
Real number (ℝ)

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct467424
Distinct (%)1.1%5.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean85.56376279.959681
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum00
Maximum704867
Zeros32441
Zeros (%)0.8%0.6%
Negative00
Negative (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
2024-12-24T10:11:33.650376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum00
5-th percentile43
Q12218
median5246
Q3116106
95-th percentile288282
Maximum704867
Range704867
Interquartile range (IQR)9488

Descriptive statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Standard deviation90.50033289.755331
Coefficient of variation (CV)1.05769461.1225074
Kurtosis2.38176753.2434149
Mean85.56376279.959681
Median Absolute Deviation (MAD)3734
Skewness1.63695371.7782196
Sum3584266590982
Variance8190.31018056.0195
MonotonicityNot monotonicNot monotonic
2024-12-24T10:11:33.836383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 579
 
1.4%
2 546
 
1.3%
6 531
 
1.3%
5 516
 
1.2%
7 514
 
1.2%
13 487
 
1.2%
9 486
 
1.2%
8 483
 
1.2%
18 481
 
1.1%
12 479
 
1.1%
Other values (457) 36788
87.8%
ValueCountFrequency (%)
7 122
 
1.7%
2 120
 
1.6%
4 119
 
1.6%
6 118
 
1.6%
13 117
 
1.6%
3 111
 
1.5%
15 110
 
1.5%
8 108
 
1.5%
20 104
 
1.4%
10 103
 
1.4%
Other values (414) 6259
84.7%
ValueCountFrequency (%)
0 324
0.8%
1 579
1.4%
2 546
1.3%
3 460
1.1%
4 478
1.1%
5 516
1.2%
6 531
1.3%
7 514
1.2%
8 483
1.2%
9 486
1.2%
ValueCountFrequency (%)
0 41
 
0.6%
1 102
1.4%
2 120
1.6%
3 111
1.5%
4 119
1.6%
5 95
1.3%
6 118
1.6%
7 122
1.7%
8 108
1.5%
9 101
1.4%
ValueCountFrequency (%)
0 41
 
0.1%
1 102
0.2%
2 120
0.3%
3 111
0.3%
4 119
0.3%
5 95
0.2%
6 118
0.3%
7 122
0.3%
8 108
0.3%
9 101
0.2%
ValueCountFrequency (%)
0 324
4.4%
1 579
7.8%
2 546
7.4%
3 460
6.2%
4 478
6.5%
5 516
7.0%
6 531
7.2%
7 514
7.0%
8 483
6.5%
9 486
6.6%

length_of_stay
Real number (ℝ)

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct323180
Distinct (%)0.8%2.4%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean23.65196919.664727
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum01
Maximum773778
Zeros90
Zeros (%)< 0.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
2024-12-24T10:11:34.003924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum01
5-th percentile33
Q155
median176
Q32923
95-th percentile8481
Maximum773778
Range773777
Interquartile range (IQR)2418

Descriptive statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Standard deviation33.76830933.995823
Coefficient of variation (CV)1.42771661.7287716
Kurtosis46.34797767.595108
Mean23.65196919.664727
Median Absolute Deviation (MAD)122
Skewness5.1738326.076089
Sum990781145342
Variance1140.29871155.716
MonotonicityNot monotonicNot monotonic
2024-12-24T10:11:34.202923image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 6020
 
14.4%
5 5803
 
13.9%
4 4537
 
10.8%
3 2301
 
5.5%
17 1630
 
3.9%
21 1243
 
3.0%
18 1197
 
2.9%
22 1162
 
2.8%
20 1147
 
2.7%
19 1109
 
2.6%
Other values (313) 15741
37.6%
ValueCountFrequency (%)
6 1591
21.5%
5 1348
18.2%
4 1031
13.9%
3 497
 
6.7%
17 193
 
2.6%
2 153
 
2.1%
18 138
 
1.9%
19 132
 
1.8%
21 130
 
1.8%
20 130
 
1.8%
Other values (170) 2048
27.7%
ValueCountFrequency (%)
0 9
 
< 0.1%
1 208
 
0.5%
2 704
 
1.7%
3 2301
 
5.5%
4 4537
10.8%
5 5803
13.9%
6 6020
14.4%
17 1630
 
3.9%
18 1197
 
2.9%
19 1109
 
2.6%
ValueCountFrequency (%)
1 49
 
0.7%
2 153
 
2.1%
3 497
 
6.7%
4 1031
13.9%
5 1348
18.2%
6 1591
21.5%
17 193
 
2.6%
18 138
 
1.9%
19 132
 
1.8%
20 130
 
1.8%
ValueCountFrequency (%)
1 49
 
0.1%
2 153
 
0.4%
3 497
 
1.2%
4 1031
2.5%
5 1348
3.2%
6 1591
3.8%
17 193
 
0.5%
18 138
 
0.3%
19 132
 
0.3%
20 130
 
0.3%
ValueCountFrequency (%)
0 9
 
0.1%
1 208
 
2.8%
2 704
 
9.5%
3 2301
 
31.1%
4 4537
61.4%
5 5803
78.5%
6 6020
81.5%
17 1630
 
22.1%
18 1197
 
16.2%
19 1109
 
15.0%

flight_hour
Real number (ℝ)

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct2424
Distinct (%)0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean9.05543099.1570829
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum00
Maximum2323
Zeros1321180
Zeros (%)3.2%2.4%
Negative00
Negative (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
2024-12-24T10:11:34.352750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum00
5-th percentile11
Q155
median99
Q31313
95-th percentile1917
Maximum2323
Range2323
Interquartile range (IQR)88

Descriptive statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Standard deviation5.44366525.2360082
Coefficient of variation (CV)0.601149220.57179871
Kurtosis-0.27249414-0.48318059
Mean9.05543099.1570829
Median Absolute Deviation (MAD)44
Skewness0.417383720.27901594
Sum37933267680
Variance29.63349127.415782
MonotonicityNot monotonicNot monotonic
2024-12-24T10:11:34.482091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
11 2670
 
6.4%
12 2663
 
6.4%
7 2658
 
6.3%
8 2647
 
6.3%
10 2640
 
6.3%
9 2590
 
6.2%
13 2547
 
6.1%
6 2528
 
6.0%
5 2388
 
5.7%
4 2367
 
5.7%
Other values (14) 16192
38.7%
ValueCountFrequency (%)
9 507
 
6.9%
13 499
 
6.8%
14 485
 
6.6%
6 482
 
6.5%
8 478
 
6.5%
12 451
 
6.1%
5 429
 
5.8%
7 422
 
5.7%
4 419
 
5.7%
10 410
 
5.5%
Other values (14) 2809
38.0%
ValueCountFrequency (%)
0 1321
3.2%
1 1787
4.3%
2 2210
5.3%
3 2232
5.3%
4 2367
5.7%
5 2388
5.7%
6 2528
6.0%
7 2658
6.3%
8 2647
6.3%
9 2590
6.2%
ValueCountFrequency (%)
0 180
 
2.4%
1 284
3.8%
2 386
5.2%
3 384
5.2%
4 419
5.7%
5 429
5.8%
6 482
6.5%
7 422
5.7%
8 478
6.5%
9 507
6.9%
ValueCountFrequency (%)
0 180
 
0.4%
1 284
0.7%
2 386
0.9%
3 384
0.9%
4 419
1.0%
5 429
1.0%
6 482
1.2%
7 422
1.0%
8 478
1.1%
9 507
1.2%
ValueCountFrequency (%)
0 1321
17.9%
1 1787
24.2%
2 2210
29.9%
3 2232
30.2%
4 2367
32.0%
5 2388
32.3%
6 2528
34.2%
7 2658
36.0%
8 2647
35.8%
9 2590
35.0%

flight_day
Categorical

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct77
Distinct (%)< 0.1%0.1%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
Mon
6794 
Tue
6442 
Wed
6332 
Thu
6214 
Fri
5709 
Other values (2)
10399 
Wed
1230 
Mon
1194 
Tue
1116 
Thu
1109 
Fri
976 
Other values (2)
1766 

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length33
Median length33
Mean length33
Min length33

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters12567022173
Distinct characters1515
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st rowSatMon
2nd rowSatMon
3rd rowWedTue
4th rowSatTue
5th rowWedTue

Common Values

ValueCountFrequency (%)
Mon 6794
16.2%
Tue 6442
15.4%
Wed 6332
15.1%
Thu 6214
14.8%
Fri 5709
13.6%
Sun 5531
13.2%
Sat 4868
11.6%
ValueCountFrequency (%)
Wed 1230
16.6%
Mon 1194
16.2%
Tue 1116
15.1%
Thu 1109
15.0%
Fri 976
13.2%
Sun 911
12.3%
Sat 855
11.6%

Length

2024-12-24T10:11:34.596603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report: Incomplete Bookings

2024-12-24T10:11:34.679831image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:34.795485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
mon 6794
16.2%
tue 6442
15.4%
wed 6332
15.1%
thu 6214
14.8%
fri 5709
13.6%
sun 5531
13.2%
sat 4868
11.6%
ValueCountFrequency (%)
wed 1230
16.6%
mon 1194
16.2%
tue 1116
15.1%
thu 1109
15.0%
fri 976
13.2%
sun 911
12.3%
sat 855
11.6%

Most occurring characters

ValueCountFrequency (%)
u 18187
14.5%
e 12774
10.2%
T 12656
10.1%
n 12325
9.8%
S 10399
 
8.3%
M 6794
 
5.4%
o 6794
 
5.4%
W 6332
 
5.0%
d 6332
 
5.0%
h 6214
 
4.9%
Other values (5) 26863
21.4%
ValueCountFrequency (%)
u 3136
14.1%
e 2346
10.6%
T 2225
10.0%
n 2105
9.5%
S 1766
 
8.0%
W 1230
 
5.5%
d 1230
 
5.5%
M 1194
 
5.4%
o 1194
 
5.4%
h 1109
 
5.0%
Other values (5) 4638
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 125670
100.0%
ValueCountFrequency (%)
(unknown) 22173
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
u 18187
14.5%
e 12774
10.2%
T 12656
10.1%
n 12325
9.8%
S 10399
 
8.3%
M 6794
 
5.4%
o 6794
 
5.4%
W 6332
 
5.0%
d 6332
 
5.0%
h 6214
 
4.9%
Other values (5) 26863
21.4%
ValueCountFrequency (%)
u 3136
14.1%
e 2346
10.6%
T 2225
10.0%
n 2105
9.5%
S 1766
 
8.0%
W 1230
 
5.5%
d 1230
 
5.5%
M 1194
 
5.4%
o 1194
 
5.4%
h 1109
 
5.0%
Other values (5) 4638
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 125670
100.0%
ValueCountFrequency (%)
(unknown) 22173
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
u 18187
14.5%
e 12774
10.2%
T 12656
10.1%
n 12325
9.8%
S 10399
 
8.3%
M 6794
 
5.4%
o 6794
 
5.4%
W 6332
 
5.0%
d 6332
 
5.0%
h 6214
 
4.9%
Other values (5) 26863
21.4%
ValueCountFrequency (%)
u 3136
14.1%
e 2346
10.6%
T 2225
10.0%
n 2105
9.5%
S 1766
 
8.0%
W 1230
 
5.5%
d 1230
 
5.5%
M 1194
 
5.4%
o 1194
 
5.4%
h 1109
 
5.0%
Other values (5) 4638
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 125670
100.0%
ValueCountFrequency (%)
(unknown) 22173
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
u 18187
14.5%
e 12774
10.2%
T 12656
10.1%
n 12325
9.8%
S 10399
 
8.3%
M 6794
 
5.4%
o 6794
 
5.4%
W 6332
 
5.0%
d 6332
 
5.0%
h 6214
 
4.9%
Other values (5) 26863
21.4%
ValueCountFrequency (%)
u 3136
14.1%
e 2346
10.6%
T 2225
10.0%
n 2105
9.5%
S 1766
 
8.0%
W 1230
 
5.5%
d 1230
 
5.5%
M 1194
 
5.4%
o 1194
 
5.4%
h 1109
 
5.0%
Other values (5) 4638
20.9%

route
['Text', 'Text']

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct786549
Distinct (%)1.9%7.4%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
2024-12-24T10:11:35.263344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length66
Median length66
Mean length66
Min length66

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters25134044346
Distinct characters2626
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique66103 ?
Unique (%)0.2%1.4%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st rowAKLDELAKLKUL
2nd rowAKLDELAKLKUL
3rd rowAKLDELAKLKUL
4th rowAKLDELAKLKUL
5th rowAKLDELAKLKUL
ValueCountFrequency (%)
aklkul 2061
 
4.9%
melsgn 790
 
1.9%
icnsin 704
 
1.7%
icnsyd 678
 
1.6%
dmkper 640
 
1.5%
meltpe 623
 
1.5%
dmkool 612
 
1.5%
dpsicn 601
 
1.4%
sgnsyd 548
 
1.3%
dmkkix 544
 
1.3%
Other values (776) 34089
81.4%
ValueCountFrequency (%)
aklkul 559
 
7.6%
pentpe 396
 
5.4%
dmkkix 185
 
2.5%
jhbktm 163
 
2.2%
melpen 136
 
1.8%
icnpen 134
 
1.8%
ktmpen 117
 
1.6%
cgkhnd 105
 
1.4%
hndpen 98
 
1.3%
cgkkix 96
 
1.3%
Other values (539) 5402
73.1%
2024-12-24T10:11:35.768628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 23777
 
9.5%
E 23056
 
9.2%
P 20416
 
8.1%
L 17961
 
7.1%
D 17852
 
7.1%
N 17685
 
7.0%
S 15759
 
6.3%
M 15202
 
6.0%
C 13511
 
5.4%
I 11430
 
4.5%
Other values (16) 74691
29.7%
ValueCountFrequency (%)
K 5208
 
11.7%
P 4183
 
9.4%
E 3982
 
9.0%
N 3705
 
8.4%
L 2681
 
6.0%
C 2318
 
5.2%
I 2312
 
5.2%
M 2264
 
5.1%
D 2184
 
4.9%
S 2083
 
4.7%
Other values (16) 13426
30.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 251340
100.0%
ValueCountFrequency (%)
(unknown) 44346
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
K 23777
 
9.5%
E 23056
 
9.2%
P 20416
 
8.1%
L 17961
 
7.1%
D 17852
 
7.1%
N 17685
 
7.0%
S 15759
 
6.3%
M 15202
 
6.0%
C 13511
 
5.4%
I 11430
 
4.5%
Other values (16) 74691
29.7%
ValueCountFrequency (%)
K 5208
 
11.7%
P 4183
 
9.4%
E 3982
 
9.0%
N 3705
 
8.4%
L 2681
 
6.0%
C 2318
 
5.2%
I 2312
 
5.2%
M 2264
 
5.1%
D 2184
 
4.9%
S 2083
 
4.7%
Other values (16) 13426
30.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 251340
100.0%
ValueCountFrequency (%)
(unknown) 44346
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
K 23777
 
9.5%
E 23056
 
9.2%
P 20416
 
8.1%
L 17961
 
7.1%
D 17852
 
7.1%
N 17685
 
7.0%
S 15759
 
6.3%
M 15202
 
6.0%
C 13511
 
5.4%
I 11430
 
4.5%
Other values (16) 74691
29.7%
ValueCountFrequency (%)
K 5208
 
11.7%
P 4183
 
9.4%
E 3982
 
9.0%
N 3705
 
8.4%
L 2681
 
6.0%
C 2318
 
5.2%
I 2312
 
5.2%
M 2264
 
5.1%
D 2184
 
4.9%
S 2083
 
4.7%
Other values (16) 13426
30.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 251340
100.0%
ValueCountFrequency (%)
(unknown) 44346
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
K 23777
 
9.5%
E 23056
 
9.2%
P 20416
 
8.1%
L 17961
 
7.1%
D 17852
 
7.1%
N 17685
 
7.0%
S 15759
 
6.3%
M 15202
 
6.0%
C 13511
 
5.4%
I 11430
 
4.5%
Other values (16) 74691
29.7%
ValueCountFrequency (%)
K 5208
 
11.7%
P 4183
 
9.4%
E 3982
 
9.0%
N 3705
 
8.4%
L 2681
 
6.0%
C 2318
 
5.2%
I 2312
 
5.2%
M 2264
 
5.1%
D 2184
 
4.9%
S 2083
 
4.7%
Other values (16) 13426
30.3%

booking_origin
['Text', 'Text']

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct10058
Distinct (%)0.2%0.8%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
2024-12-24T10:11:36.034625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length2020
Median length1615
Mean length8.29207457.9238263
Min length44

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters34735558565
Distinct characters5350
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique2416 ?
Unique (%)0.1%0.2%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st rowNew ZealandMalaysia
2nd rowNew ZealandMalaysia
3rd rowIndiaSingapore
4th rowNew ZealandMalaysia
5th rowIndiaMalaysia
ValueCountFrequency (%)
australia 16796
35.0%
malaysia 4621
 
9.6%
south 4046
 
8.4%
korea 4043
 
8.4%
japan 3347
 
7.0%
china 2600
 
5.4%
taiwan 1822
 
3.8%
indonesia 1708
 
3.6%
thailand 1529
 
3.2%
india 1130
 
2.4%
Other values (106) 6342
 
13.2%
ValueCountFrequency (%)
malaysia 2434
30.0%
australia 895
 
11.0%
china 684
 
8.4%
indonesia 609
 
7.5%
japan 472
 
5.8%
thailand 464
 
5.7%
south 459
 
5.6%
korea 459
 
5.6%
singapore 295
 
3.6%
taiwan 220
 
2.7%
Other values (58) 1134
14.0%
2024-12-24T10:11:36.427159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 75531
21.7%
i 33166
9.5%
l 24429
 
7.0%
s 24012
 
6.9%
t 22774
 
6.6%
r 22251
 
6.4%
u 21410
 
6.2%
n 17915
 
5.2%
A 16878
 
4.9%
o 11397
 
3.3%
Other values (43) 77592
22.3%
ValueCountFrequency (%)
a 14333
24.5%
i 6326
10.8%
s 4137
 
7.1%
n 4120
 
7.0%
l 3948
 
6.7%
M 2547
 
4.3%
y 2473
 
4.2%
o 2049
 
3.5%
e 1967
 
3.4%
t 1804
 
3.1%
Other values (40) 14861
25.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 347355
100.0%
ValueCountFrequency (%)
(unknown) 58565
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 75531
21.7%
i 33166
9.5%
l 24429
 
7.0%
s 24012
 
6.9%
t 22774
 
6.6%
r 22251
 
6.4%
u 21410
 
6.2%
n 17915
 
5.2%
A 16878
 
4.9%
o 11397
 
3.3%
Other values (43) 77592
22.3%
ValueCountFrequency (%)
a 14333
24.5%
i 6326
10.8%
s 4137
 
7.1%
n 4120
 
7.0%
l 3948
 
6.7%
M 2547
 
4.3%
y 2473
 
4.2%
o 2049
 
3.5%
e 1967
 
3.4%
t 1804
 
3.1%
Other values (40) 14861
25.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 347355
100.0%
ValueCountFrequency (%)
(unknown) 58565
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 75531
21.7%
i 33166
9.5%
l 24429
 
7.0%
s 24012
 
6.9%
t 22774
 
6.6%
r 22251
 
6.4%
u 21410
 
6.2%
n 17915
 
5.2%
A 16878
 
4.9%
o 11397
 
3.3%
Other values (43) 77592
22.3%
ValueCountFrequency (%)
a 14333
24.5%
i 6326
10.8%
s 4137
 
7.1%
n 4120
 
7.0%
l 3948
 
6.7%
M 2547
 
4.3%
y 2473
 
4.2%
o 2049
 
3.5%
e 1967
 
3.4%
t 1804
 
3.1%
Other values (40) 14861
25.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 347355
100.0%
ValueCountFrequency (%)
(unknown) 58565
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 75531
21.7%
i 33166
9.5%
l 24429
 
7.0%
s 24012
 
6.9%
t 22774
 
6.6%
r 22251
 
6.4%
u 21410
 
6.2%
n 17915
 
5.2%
A 16878
 
4.9%
o 11397
 
3.3%
Other values (43) 77592
22.3%
ValueCountFrequency (%)
a 14333
24.5%
i 6326
10.8%
s 4137
 
7.1%
n 4120
 
7.0%
l 3948
 
6.7%
M 2547
 
4.3%
y 2473
 
4.2%
o 2049
 
3.5%
e 1967
 
3.4%
t 1804
 
3.1%
Other values (40) 14861
25.4%
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
1
27425 
0
14465 
1
5506 
0
1885 

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters418907391
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st row10
2nd row01
3rd row11
4th row01
5th row10

Common Values

ValueCountFrequency (%)
1 27425
65.5%
0 14465
34.5%
ValueCountFrequency (%)
1 5506
74.5%
0 1885
 
25.5%

Length

2024-12-24T10:11:36.518521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report: Incomplete Bookings

2024-12-24T10:11:36.580470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:36.637988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1 27425
65.5%
0 14465
34.5%
ValueCountFrequency (%)
1 5506
74.5%
0 1885
 
25.5%

Most occurring characters

ValueCountFrequency (%)
1 27425
65.5%
0 14465
34.5%
ValueCountFrequency (%)
1 5506
74.5%
0 1885
 
25.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 27425
65.5%
0 14465
34.5%
ValueCountFrequency (%)
1 5506
74.5%
0 1885
 
25.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 27425
65.5%
0 14465
34.5%
ValueCountFrequency (%)
1 5506
74.5%
0 1885
 
25.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 27425
65.5%
0 14465
34.5%
ValueCountFrequency (%)
1 5506
74.5%
0 1885
 
25.5%
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
0
29909 
1
11981 
0
4803 
1
2588 

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters418907391
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st row00
2nd row00
3rd row10
4th row00
5th row00

Common Values

ValueCountFrequency (%)
0 29909
71.4%
1 11981
28.6%
ValueCountFrequency (%)
0 4803
65.0%
1 2588
35.0%

Length

2024-12-24T10:11:36.717809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report: Incomplete Bookings

2024-12-24T10:11:36.799458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:36.830608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 29909
71.4%
1 11981
28.6%
ValueCountFrequency (%)
0 4803
65.0%
1 2588
35.0%

Most occurring characters

ValueCountFrequency (%)
0 29909
71.4%
1 11981
28.6%
ValueCountFrequency (%)
0 4803
65.0%
1 2588
35.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 29909
71.4%
1 11981
28.6%
ValueCountFrequency (%)
0 4803
65.0%
1 2588
35.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 29909
71.4%
1 11981
28.6%
ValueCountFrequency (%)
0 4803
65.0%
1 2588
35.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 29909
71.4%
1 11981
28.6%
ValueCountFrequency (%)
0 4803
65.0%
1 2588
35.0%
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct22
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
0
24248 
1
17642 
0
4008 
1
3383 

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters418907391
Distinct characters22
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st row00
2nd row00
3rd row01
4th row11
5th row10

Common Values

ValueCountFrequency (%)
0 24248
57.9%
1 17642
42.1%
ValueCountFrequency (%)
0 4008
54.2%
1 3383
45.8%

Length

2024-12-24T10:11:36.914918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report: Incomplete Bookings

2024-12-24T10:11:36.988512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:37.020721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24248
57.9%
1 17642
42.1%
ValueCountFrequency (%)
0 4008
54.2%
1 3383
45.8%

Most occurring characters

ValueCountFrequency (%)
0 24248
57.9%
1 17642
42.1%
ValueCountFrequency (%)
0 4008
54.2%
1 3383
45.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24248
57.9%
1 17642
42.1%
ValueCountFrequency (%)
0 4008
54.2%
1 3383
45.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24248
57.9%
1 17642
42.1%
ValueCountFrequency (%)
0 4008
54.2%
1 3383
45.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24248
57.9%
1 17642
42.1%
ValueCountFrequency (%)
0 4008
54.2%
1 3383
45.8%

flight_duration
Real number (ℝ)

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct2121
Distinct (%)0.1%0.3%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean7.3469326.9004749
 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum4.674.67
Maximum9.59.5
Zeros00
Zeros (%)0.0%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
2024-12-24T10:11:37.096504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Minimum4.674.67
5-th percentile4.724.67
Q15.625.52
median7.576.62
Q38.838.67
95-th percentile8.838.83
Maximum9.59.5
Range4.834.83
Interquartile range (IQR)3.213.15

Descriptive statistics

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Standard deviation1.48066891.5281767
Coefficient of variation (CV)0.201535680.22145964
Kurtosis-1.3420454-1.4050642
Mean7.3469326.9004749
Median Absolute Deviation (MAD)1.261.55
Skewness-0.4194776-0.04400649
Sum307762.9851001.41
Variance2.19238052.3353239
MonotonicityNot monotonicNot monotonic
2024-12-24T10:11:37.229278image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
8.83 12668
30.2%
8.58 6354
15.2%
5.62 4950
 
11.8%
6.62 3859
 
9.2%
7 2587
 
6.2%
7.57 2287
 
5.5%
4.67 2032
 
4.9%
6.42 1339
 
3.2%
5.33 1125
 
2.7%
6.33 984
 
2.3%
Other values (11) 3705
 
8.8%
ValueCountFrequency (%)
8.83 1671
22.6%
6.62 799
10.8%
7 727
9.8%
4.67 667
 
9.0%
8.58 538
 
7.3%
5.62 514
 
7.0%
7.57 498
 
6.7%
4.75 416
 
5.6%
5.33 381
 
5.2%
6.42 369
 
5.0%
Other values (11) 811
11.0%
ValueCountFrequency (%)
4.67 2032
4.9%
4.72 369
 
0.9%
4.75 830
 
2.0%
4.83 126
 
0.3%
5 180
 
0.4%
5.07 382
 
0.9%
5.13 88
 
0.2%
5.33 1125
 
2.7%
5.52 612
 
1.5%
5.62 4950
11.8%
ValueCountFrequency (%)
4.67 667
9.0%
4.72 117
 
1.6%
4.75 416
5.6%
4.83 19
 
0.3%
5 57
 
0.8%
5.07 119
 
1.6%
5.13 28
 
0.4%
5.33 381
5.2%
5.52 52
 
0.7%
5.62 514
7.0%
ValueCountFrequency (%)
4.67 667
1.6%
4.72 117
 
0.3%
4.75 416
1.0%
4.83 19
 
< 0.1%
5 57
 
0.1%
5.07 119
 
0.3%
5.13 28
 
0.1%
5.33 381
0.9%
5.52 52
 
0.1%
5.62 514
1.2%
ValueCountFrequency (%)
4.67 2032
27.5%
4.72 369
 
5.0%
4.75 830
 
11.2%
4.83 126
 
1.7%
5 180
 
2.4%
5.07 382
 
5.2%
5.13 88
 
1.2%
5.33 1125
 
15.2%
5.52 612
 
8.3%
5.62 4950
67.0%

booking_complete
Categorical

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Distinct11
Distinct (%)< 0.1%< 0.1%
Missing00
Missing (%)0.0%0.0%
Memory size654.5 KiB115.5 KiB
0
41890 
1
7391 

Length

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Total characters418907391
Distinct characters11
Distinct categories11 ?
Distinct scripts11 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
Unique00 ?
Unique (%)0.0%0.0%

Sample

 Profiling Report: Incomplete BookingsProfiling Report: Complete Bookings
1st row01
2nd row01
3rd row01
4th row01
5th row01

Common Values

ValueCountFrequency (%)
0 41890
100.0%
ValueCountFrequency (%)
1 7391
100.0%

Length

2024-12-24T10:11:37.335464image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

Profiling Report: Incomplete Bookings

2024-12-24T10:11:37.400257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:37.426270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 41890
100.0%
ValueCountFrequency (%)
1 7391
100.0%

Most occurring characters

ValueCountFrequency (%)
0 41890
100.0%
ValueCountFrequency (%)
1 7391
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 41890
100.0%
ValueCountFrequency (%)
1 7391
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 41890
100.0%
ValueCountFrequency (%)
1 7391
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41890
100.0%
ValueCountFrequency (%)
(unknown) 7391
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 41890
100.0%
ValueCountFrequency (%)
1 7391
100.0%

Interactions

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.200701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:31.105499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:24.717234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:28.982224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.350257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.532880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.888841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.058898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:26.466247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.610845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.298947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:31.205854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:24.902170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.090340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.463547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.653874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:26.000017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.170974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:26.579974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.711963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.410182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:31.289037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.015407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.196769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.572432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.740708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:26.117320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.285254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:26.689681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.812658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.529564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:31.398428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.133104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.307281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.680655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.856288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:26.235423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.405860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.010962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.916197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.617213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:31.488473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.234082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.414162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:25.787381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:29.965975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:26.355888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:30.509565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.097915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:31.006121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

Profiling Report: Incomplete Bookings

2024-12-24T10:11:37.522316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Complete Bookings

2024-12-24T10:11:37.729721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Profiling Report: Incomplete Bookings

flight_dayflight_durationflight_hourlength_of_staynum_passengerspurchase_leadsales_channeltrip_typewants_extra_baggagewants_in_flight_mealswants_preferred_seat
flight_day1.0000.0190.0280.0070.0150.0520.0500.0040.0000.0060.012
flight_duration0.0191.000-0.0310.241-0.0630.0670.0720.0320.1150.1770.130
flight_hour0.028-0.0311.000-0.0470.0250.0380.0340.0060.0300.0280.033
length_of_stay0.0070.241-0.0471.000-0.1210.0250.0310.0000.1080.0700.037
num_passengers0.015-0.0630.025-0.1211.0000.2550.0140.0000.1300.0260.052
purchase_lead0.0520.0670.0380.0250.2551.0000.0210.0000.0650.0450.021
sales_channel0.0500.0720.0340.0310.0140.0211.0000.0240.0560.0310.029
trip_type0.0040.0320.0060.0000.0000.0000.0241.0000.0180.0130.004
wants_extra_baggage0.0000.1150.0300.1080.1300.0650.0560.0181.0000.2220.209
wants_in_flight_meals0.0060.1770.0280.0700.0260.0450.0310.0130.2221.0000.310
wants_preferred_seat0.0120.1300.0330.0370.0520.0210.0290.0040.2090.3101.000

Profiling Report: Complete Bookings

flight_dayflight_durationflight_hourlength_of_staynum_passengerspurchase_leadsales_channeltrip_typewants_extra_baggagewants_in_flight_mealswants_preferred_seat
flight_day1.0000.0210.0320.0000.0230.0590.0200.0170.0000.0000.028
flight_duration0.0211.0000.0140.145-0.0130.1260.0460.1400.0580.1500.141
flight_hour0.0320.0141.000-0.0450.0260.0700.0170.0120.0260.0260.000
length_of_stay0.0000.145-0.0451.000-0.1280.0240.0000.0000.0850.0360.010
num_passengers0.023-0.0130.026-0.1281.0000.2690.0000.0550.1370.0390.067
purchase_lead0.0590.1260.0700.0240.2691.0000.0250.0000.0090.0220.000
sales_channel0.0200.0460.0170.0000.0000.0251.0000.0000.0300.0140.043
trip_type0.0170.1400.0120.0000.0550.0000.0001.0000.0310.0000.000
wants_extra_baggage0.0000.0580.0260.0850.1370.0090.0300.0311.0000.1740.188
wants_in_flight_meals0.0000.1500.0260.0360.0390.0220.0140.0000.1741.0000.336
wants_preferred_seat0.0280.1410.0000.0100.0670.0000.0430.0000.1880.3361.000

Missing values

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.757301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.

Profiling Report: Complete Bookings

2024-12-24T10:11:31.647859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.

Profiling Report: Incomplete Bookings

2024-12-24T10:11:27.958836image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Profiling Report: Complete Bookings

2024-12-24T10:11:31.795624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Profiling Report: Incomplete Bookings

num_passengerssales_channeltrip_typepurchase_leadlength_of_stayflight_hourflight_dayroutebooking_originwants_extra_baggagewants_preferred_seatwants_in_flight_mealsflight_durationbooking_complete
02InternetRoundTrip262197SatAKLDELNew Zealand1005.520
11InternetRoundTrip112203SatAKLDELNew Zealand0005.520
22InternetRoundTrip2432217WedAKLDELIndia1105.520
31InternetRoundTrip96314SatAKLDELNew Zealand0015.520
42InternetRoundTrip682215WedAKLDELIndia1015.520
51InternetRoundTrip34820ThuAKLDELNew Zealand1015.520
63InternetRoundTrip201336ThuAKLDELNew Zealand1015.520
72InternetRoundTrip2381914MonAKLDELIndia1015.520
81InternetRoundTrip80224MonAKLDELNew Zealand0015.520
91MobileRoundTrip3783012SunAKLDELIndia0005.520

Profiling Report: Complete Bookings

num_passengerssales_channeltrip_typepurchase_leadlength_of_stayflight_hourflight_dayroutebooking_originwants_extra_baggagewants_preferred_seatwants_in_flight_mealsflight_durationbooking_complete
821InternetRoundTrip153117MonAKLKULMalaysia0008.831
861InternetRoundTrip1561914MonAKLKULMalaysia1008.831
941InternetRoundTrip181872TueAKLKULSingapore1018.831
1091MobileRoundTrip1271716TueAKLKULMalaysia1018.831
1221InternetRoundTrip421714TueAKLKULMalaysia0008.831
1241InternetRoundTrip2218013ThuAKLKULMalaysia1008.831
1363InternetRoundTrip2291713MonAKLKULMalaysia1118.831
1521InternetRoundTrip109123TueAKLKULSingapore1008.831
1581InternetRoundTrip992113SunAKLKULSingapore0008.831
1681InternetRoundTrip1421249WedAKLKULMalaysia1008.831

Profiling Report: Incomplete Bookings

num_passengerssales_channeltrip_typepurchase_leadlength_of_stayflight_hourflight_dayroutebooking_originwants_extra_baggagewants_preferred_seatwants_in_flight_mealsflight_durationbooking_complete
499901InternetRoundTrip12610SatPERPNHAustralia0005.620
499911InternetRoundTrip866MonPERPNHAustralia0105.620
499921InternetRoundTrip14612FriPERPNHAustralia1005.620
499931InternetRoundTrip19612SunPERPNHAustralia1005.620
499942InternetRoundTrip2569SunPERPNHAustralia0005.620
499952InternetRoundTrip2769SatPERPNHAustralia1015.620
499961InternetRoundTrip11164SunPERPNHAustralia0005.620
499971InternetRoundTrip24622SatPERPNHAustralia0015.620
499981InternetRoundTrip15611MonPERPNHAustralia1015.620
499991InternetRoundTrip19610ThuPERPNHAustralia0105.620

Profiling Report: Complete Bookings

num_passengerssales_channeltrip_typepurchase_leadlength_of_stayflight_hourflight_dayroutebooking_originwants_extra_baggagewants_preferred_seatwants_in_flight_mealsflight_durationbooking_complete
499662InternetRoundTrip2360ThuPENTPEItaly1114.671
499673InternetRoundTrip279613FriPENTPEMalaysia1004.671
499681InternetRoundTrip25612FriPENTPETaiwan0004.671
499702InternetRoundTrip52610SunPENTPEMalaysia1114.671
499712MobileRoundTrip3861SatPENTPEMalaysia0014.671
499721InternetRoundTrip3366WedPENTPETaiwan1104.671
499772InternetRoundTrip15616TuePENTPEMalaysia1114.671
499804InternetRoundTrip24269TuePENXIYMalaysia1015.001
499842InternetRoundTrip764WedPERPNHAustralia0005.621
499873InternetRoundTrip243612FriPERPNHAustralia1015.621

Duplicate rows

Profiling Report: Incomplete Bookings

num_passengerssales_channeltrip_typepurchase_leadlength_of_stayflight_hourflight_dayroutebooking_originwants_extra_baggagewants_preferred_seatwants_in_flight_mealsflight_durationbooking_complete# duplicates
Dataset does not contain duplicate rows.

Profiling Report: Complete Bookings

num_passengerssales_channeltrip_typepurchase_leadlength_of_stayflight_hourflight_dayroutebooking_originwants_extra_baggagewants_preferred_seatwants_in_flight_mealsflight_durationbooking_complete# duplicates
Dataset does not contain duplicate rows.